Regression analysis of dengue cases with meteorological factors in the National Capital Region using different mathematical models
Abstract
We develop three regression models (linear, power law, and exponential) and determine the associations of weekly meteorological data to weekly dengue cases in the National Capital Region (NCR) from 2009 to 2019. We show that among the three models, the linear model best relates the variation of dengue cases with meteorological data. The linear model reveals that dengue cases are negatively associated with maximum temperature, while dengue cases are positively associated with minimum temperature and relative humidity. Mean temperature, rainfall, wind speed, and wind direction also show association with the dengue cases. In addition, meteorological data from Science Garden weather station generate best models with three regression methods, which suggests that it is the best source when modeling dengue cases in NCR than the other weather stations.
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